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PubMed2026

Molecular Pathways, Target Landscape, and Translational Models in Heart Failure with Preserved Ejection Fraction.

Heart failure with preserved ejection fraction (HFpEF) is a substantial global health burden and the greatest unmet medical need for cardiovascular diseases. It is marked by pronounced clinical heterogeneity and complex multi-system pathophysiology with limited therapeutic options. Progress in developing effective therapeutics is constrained by the inadequacy of experimental models to fully recapitulate the multifactorial nature of the disease. Recent evidence underscores the significant involvement of inflammatory, oxidative, and mitochondrial pathways in the pathogenesis of HFpEF, with non-coding RNAs and epigenetic regulation serving as crucial modulators and prospective therapeutic targets. This review maps the HFpEF target landscape, while critically assessing the mechanistic contributions, translational fidelity, and limitations of existing in vivo and in vitro models. Further, advances are noted among the in vitro technologies, including human cardiac organoids and engineered heart tissues integrated with high-throughput multi-omics and computational modeling, enabling in-depth examination of HFpEF mechanisms. Finally, we underscore the necessity of integrative, systems-level approaches and multi-marker strategies to enhance translational relevance, improve risk stratification, and accelerate development of mechanism-based therapies. Collectively, this review supports phenotypic-guided and mechanism-informed therapeutic development for HFpEF, and provides a roadmap for next generation model development and therapeutic innovation.

Humans↗

PubMed2026

A Comparative Analysis of the Methylation Status of Non-Coding RNA Promoters in Fibroid and Matched Myometrium.

Uterine fibroids exhibit dysregulated expression of non-coding RNAs (ncRNAs), although the underlying mechanisms remain incompletely understood. We investigated promoter DNA methylation and its relationship with ncRNA expression in fibroids. Genomic DNA from eight paired fibroid and matched myometrial tissues was analyzed using MeDIP-chip to identify differentially methylated ncRNA promoters. Selected candidates were validated by methylation-specific PCR (MSP) in 16 paired samples, and transcript expression was assessed by qRT-PCR in 68-94 paired specimens. MeDIP-chip identified 538 lncRNAs and 61 miRNAs with differential promoter methylation, including 300 hypermethylated and 238 hypomethylated lncRNAs and 47 hypermethylated and 14 hypomethylated miRNAs. Promoter methylation was not significantly correlated with transcript expression (r = -0.1224). MSP confirmed hypermethylation of LINC-PINT and MIR9-3 and hypomethylation of WT1-AS and TTLL10-AS1. Correspondingly, LINC-PINT and MIR9-3 expression was decreased, whereas WT1-AS and TTLL10-AS1 expression was increased in fibroids. However, LINC-PINT and TTLL10-AS1 methylation did not fully correspond with MeDIP-chip findings. These results reveal widespread ncRNA promoter methylation alterations in uterine fibroids but demonstrate that genome-wide methylation does not consistently predict transcript expression, highlighting the complexity of ncRNA epigenetic regulation and the importance of locus-specific validation.

Humans↗

PubMed2026

LINC01871-Mediated Sensitivity to Cyclin-Dependent Kinase 4/6 Inhibitors in Human Breast Cancer.

Breast cancer remains the most frequently diagnosed malignancy in women, and resistance to cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors limits long-term treatment efficacy. This study aimed to identify long non-coding RNAs (lncRNAs) associated with predicted sensitivity to CDK4/6 inhibitors and to investigate their biological functions in breast cancer. Transcriptomic data from The Cancer Genome Atlas (TCGA) and drug sensitivity data from the Genomics of Drug Sensitivity in Cancer 2 (GDSC2) database were integrated, and drug sensitivity was predicted using the oncoPredict algorithm. Candidate lncRNAs were identified through differential expression analysis, weighted gene co-expression network analysis, prognostic analysis, and machine learning. The biological functions of LINC01871 were subsequently evaluated using in vitro and in vivo experiments. Sixty-two lncRNAs associated with predicted sensitivity to ribociclib and palbociclib were identified, and six core lncRNAs were selected. LINC01871 showed the highest discriminatory performance for predicted drug sensitivity. Overexpression of LINC01871 was associated with increased sensitivity of breast cancer cells to ribociclib and palbociclib, inhibition of cell proliferation, promotion of apoptosis, and suppression of nuclear factor kappa B (NF-κB) signaling. Single-cell transcriptomic analysis demonstrated high LINC01871 expression in T cells and natural killer (NK) cells, while transcriptome-based immune infiltration analyses showed that high LINC01871 expression was associated with increased immune infiltration. These findings identify LINC01871 as a candidate biomarker of sensitivity to CDK4/6 inhibitors and demonstrate its tumor-suppressive effects in breast cancer. Further clinical and mechanistic studies are required to validate its predictive value and therapeutic relevance.

Humans↗

PubMed2026

LncRNA DNAJC3-AS1 promotes gastric cancer malignancy through miR-576-5p-mediated upregulation of LYPLA1.

Long non-coding RNAs (lncRNAs) are involved in tumor progression, but the role of lnc-DNAJC3-AS1 in gastric cancer (GC) remains unclear. This study aimed to investigate the biological function and regulatory mechanism of lnc-DNAJC3-AS1 in GC. Reverse transcription quantitative PCR (RT-qPCR) was used to detect the expression levels of lnc-DNAJC3-AS1, miR-576-5p, and LYPLA1, and Western blot was used to analyze protein expression. The Cancer Genome Atlas (TCGA) database and clinical samples were used to evaluate their clinical relevance. Cell viability, cell cycle distribution, apoptosis, migration, and invasion were assessed using Cell Counting Kit-8 (CCK-8), flow cytometry, wound-healing, Transwell, and immunofluorescence assays. Dual-luciferase reporter assay, RNA immunoprecipitation (RIP), fluorescence in situ hybridization (FISH), and rescue assays were performed to explore the potential regulatory relationship among lnc-DNAJC3-AS1, miR-576-5p, and LYPLA1. A xenograft tumor model was also established to evaluate the role of lnc-DNAJC3-AS1 in vivo. The results showed that lnc-DNAJC3-AS1 and LYPLA1 were upregulated, whereas miR-576-5p was downregulated in GC tissues and cells. Knockdown of lnc-DNAJC3-AS1 inhibited GC cell viability, migration, and invasion, induced G0/G1 phase arrest and apoptosis, and suppressed tumor growth in vivo. Mechanistically, lnc-DNAJC3-AS1 was mainly localized in the cytoplasm and was associated with miR-576-5p-related RNA-induced silencing complex (RISC) complexes. MiR-576-5p targeted LYPLA1, and restoration of miR-576-5p or knockdown of LYPLA1 partially attenuated the effects of lnc-DNAJC3-AS1 overexpression on GC cell phenotypes and LYPLA1 enzymatic activity. These findings suggest that lnc-DNAJC3-AS1 promotes GC progression, at least in part, through the miR-576-5p/LYPLA1 pathway, providing a potential target for GC treatment.

Gastric cancer↗

PubMed2026

Cancer-associated fusion transcripts: mechanisms, functional roles, and clinical implications.

Fusion transcripts are hybrid RNA molecules generated through genomic rearrangements or RNA-level fusion mechanisms. They represent important molecular features of many cancers and can function as oncogenic drivers, diagnostic biomarkers, prognostic indicators, and therapeutic targets. Since the discovery of the BCR::ABL1 fusion in chronic myeloid leukemia, numerous cancer-associated fusion transcripts have been identified across hematologic malignancies and solid tumors. These fusion events encompass diverse biological mechanisms, including constitutively active kinases, aberrant transcription factors, epigenetic regulators, and non-coding fusion RNAs. This review summarizes current knowledge of the mechanisms underlying fusion transcript formation, including genomic rearrangement-dependent and rearrangement-independent processes, as well as fusion circular RNAs. The functional roles of fusion transcripts in cancer biology and their clinical relevance as diagnostic, prognostic, and predictive biomarkers are discussed. In addition, recent advances in fusion transcript detection and characterization are reviewed, including next-generation sequencing, long-read sequencing, single-cell approaches, artificial intelligence-assisted computational methods, and CRISPR/Cas9-mediated strategies for functional modeling and functional validation of fusion transcripts. Despite the rapid expansion of fusion transcript catalogs, the biological and clinical significance of most identified fusion events remains incompletely understood. Future progress will depend on integrating advanced sequencing technologies, artificial intelligence-assisted computational prioritization, and systematic functional validation to distinguish clinically actionable fusion transcripts from biologically neutral events. Such multidisciplinary approaches will be essential for translating fusion transcript research into precision oncology and improving cancer diagnosis, patient stratification, and targeted therapy.

Humans↗

PubMed2026

Deletion of the MALAT1 RNA 3' end promotes transcript decay and inhibits proliferation in gastric and breast cancer cells.

The long non-coding RNA MALAT1 is a conserved oncogenic driver whose function relies on a 3' triple-helix motif. While its biochemistry is well-characterized in vitro, the endogenous requirement for this motif in regulating the stability of the transcript and other genes residing in its locus remains unclear. In this study, we employed a dual-sgRNA CRISPR-Cas9 approach to systematically excise triple-helix-forming sequences from the native MALAT1 locus in gastric (AGS) and breast (MCF7) cancer cells. Our findings demonstrate that the 3' end strongly contributes to MALAT1 stability. Perturbations ranging from genomic deletions to a single-base changes trigger transcript collapse and rapid exonucleolytic decay, while the biogenesis of the small RNA mascRNA (a byproduct of MALAT1, also involved in cancer) remains decoupled and unaffected. In cellulo, DMS probing reveals that edited transcripts retain structural complexity in the 3' region. Phenotypically, structural disruption of the 3' end significantly impairs proliferation of both cancer cellular models. These results identify the 3' triple-helix as a determinant of MALAT1 stability and provide endogenous validation for its role in the analyzed AGS and MCF7 cells.

Cancer↗

PubMed2026

PCBP2 facilitates miR-93-5p-mediated repression of GDF11 in HCC cell lines.

Growth differentiation factor 11 (GDF11), a member of the transforming growth factor-β superfamily, functions in skeletal muscle and neuronal regeneration and has been implicated in tumor suppression. In hepatocellular carcinoma (HCC), GDF11 expression is markedly downregulated, but the mechanisms responsible for this repression remain unclear. In this study, we examined whether the oncogenic miR-106b-25 cluster contributes to GDF11 suppression in HCC. We found that this cluster decreases GDF11 expression at both the mRNA and protein levels, with miR-93-5p acting as the dominant regulator. Inhibition of miR-93-5p with antisense oligonucleotides restored GDF11 expression and reduced HCC cell proliferation, migration, and invasion. Mechanistically, we identified the RNA-binding protein (RBP) PCBP2 as a key facilitator of miR-93-5p targeting of GDF11. PCBP2 binds a C-rich element adjacent to the miR-93-5p target site in the GDF11 3' UTR, thereby enhancing miR-93-5p-mediated repression. PCBP2 knockout attenuated miR-93-5p-mediated repression, whereas re-expression of PCBP2 restored it, supporting its modulatory role. Collectively, these findings identify PCBP2 as a modulator of miR-93-5p-mediated GDF11 repression and suggest that this regulatory interaction contributes to HCC cell proliferation, migration, and invasion. This work provides insights into the post-transcriptional control of the tumor suppressor and highlights the therapeutic potential of targeting miRNA-RBP interactions.

GDF11↗

PubMed2026

The dark genome in cardiovascular medicine.

Only ∼1%-2% of the human genome directly codes for proteins. The remainder consists of non-coding DNA, often referred to as the 'dark genome'. This includes regulatory elements, transposable and repetitive sequences, structural genomic features, pseudogenes, intronic and intergenic regions, and non-coding RNA (ncRNA) genes. These components are increasingly recognized as major regulators of gene expression, cell identity, and disease susceptibility. Currently, dark genome elements, particularly ncRNAs are increasingly recognized as important regulators of cardiovascular health and disease. Advances in genome analysis technologies have greatly improved our understanding of these non-coding regions and revealed clearer connections between the dark genome and cardiovascular traits. This review highlights major parts of the dark genome involved in cardiovascular disease, with emphasis on those for which mechanistic understanding and translational relevance are beginning to emerge. As mechanistic insight into individual and collective components of the dark genome advances, it increasingly enables the development of new opportunities for targeted therapeutics for cardiovascular prevention and disease management.

Humans↗

PubMed2026

A structural bridge between dengue virus tandem xrRNAs facilitates coordination of exonuclease resistance.

Orthoflavivirus RNA genomes resist host 5'-3' exoribonucleases to produce subgenomic flaviviral RNAs (sfRNAs). This resistance is conferred by exoribonuclease-resistant RNA (xrRNA) structures within the viral 3' untranslated region that often occur in tandem, and whose function can be coupled. In dengue virus serotype 2 (DENV2), this coupling results in changing patterns of sfRNA identity and abundance associated with the ability of the virus to adapt to host vs. vector infections. The physical basis of this coupling was unknown. Using a combination of virology, biochemistry, bioinformatics, structural biology, and biophysics, we explored the structural and sequence determinants of tandem xrRNA coupling in DENV2. We discovered that the spatial proximity, order, and structural integrity of the tandem xrRNAs are all important for coupling. Furthermore, an unpaired A-rich linker that lies between the two xrRNAs is essential in stabilizing a specific structure that correlates to coupling. This A-rich sequence likely forms tertiary contacts with an adjacent stem-loop structure to form a physical bridge between the two xrRNAs, a finding that is supported by a mid-resolution cryo-electron microscopy (cryo-EM) map of the DENV2 tandem xrRNAs. Disruption of the structure of this bridge by mutation changes the relative orientation or spacing between the tandem xrRNAs, which is correlated to their functional coupling. These findings help provide an explanation for the coupling between tandem xrRNAs, suggesting a new mechanistic hypothesis in which the two tandem xrRNAs can simultaneously encounter Xrn1.IMPORTANCEDengue virus (DENV) generates non-coding subgenomic flaviviral RNAs (sfRNAs) that affect several cellular pathways and are important for successful infection. These sfRNAs are formed by structured RNA elements in the viral genome called exoribonuclease-resistant RNAs (xrRNAs), which fold into a distinct three-dimensional topology to block degradation by host cell exoribonucleases and often occur in tandem. Specific patterns of sfRNAs made during infection are important for host vs. vector fitness, and in DENV2, this pattern depends on functional coupling between tandem xrRNAs. However, the source of this functional coupling was unknown. We determined that an unpaired A-rich linker between the tandem xrRNAs is necessary for creating a structural bridge between the tandem xrRNAs. This bridge appears to favor a specific orientation between the tandem xrRNAs that is correlated to coupling and therefore to the patterns and relative abundance of sfRNAs produced during infection.

Dengue Virus↗

PubMed2025

The small nucleolar RNA NON-CODING RNA 1 negatively regulates drought tolerance in Arabidopsis thaliana.

Small nucleolar RNAs (snoRNAs) function in ribosome biogenesis, and many ribosome biogenesis-related genes were downregulated by osmotic stress, implying a negative role of snoRNAs in drought tolerance. A snoRNA, namely, the NON-CODING RNA 1 (NCR1) was studied for its roles in drought tolerance in Arabidopsis. In comparison with wild-type (WT) plants, the loss-of-function ncr1 mutant plants showed enhanced drought tolerance, which was restored in the NCR1-complemented plants, whereas the NCR1-overexpressing plants revealed a drought-sensitive phenotype. Physiological analyses revealed that the ncr1 plants had a higher leaf surface temperature, lower water loss rates, and improved cell membrane integrity compared with WT. Comparative leaf transcriptomics and proteomics suggested that wax biosynthesis, anthocyanin metabolism, and leaf senescence processes are regulated by NCR1 under both normal and water-deficit conditions. Under drought, an increase in wax and anthocyanin accumulations and a delay in leaf senescence in ncr1 plants, when compared with WT, supported the transcriptome and proteomics data. Additionally, the ncr1 plants exhibited higher abscisic acid (ABA) sensitivity and longer root hairs than WT. Collectively, our results suggest that NCR1 negatively regulates drought tolerance through modification of wax biosynthesis, anthocyanin accumulation, leaf senescence, cell membrane integrity, ABA responses, and root hair development.

Arabidopsis↗

PubMed2026

Epigenetic alterations in rheumatoid arthritis: multilayer mechanisms and translational opportunities.

Rheumatoid arthritis (RA) is a chronic inflammatory disease driven by immune dysregulation, in which genetic susceptibility and environmental exposures promote persistent synovitis, progressive joint damage, and systemic comorbidities. Recent epigenomic studies show several recurring abnormalities. Many RA susceptibility variants lie outside protein-coding sequence and map to immune-cell and synovial fibroblast regulatory elements, linking inherited risk to enhancer activity, methylation quantitative trait effects, and distal gene control. Blood-based epigenome-wide association studies identify disease-associated DNA methylation signatures, but these signals require careful control for leukocyte composition, smoking, treatment exposure, and disease stage. RA fibroblast-like synoviocytes also display stable methylome remodeling, including relative hypomethylation at loci involved in inflammation, migration, matrix degradation, and apoptosis resistance, while TET3-associated 5-hydroxymethylcytosine has emerged as a functional contributor to chemokine production and invasive stromal behavior. Histone modifications, chromatin accessibility, and 3D genome organization define pathogenic regulatory states and connect non-coding risk loci to effector genes in immune and stromal compartments. Finally, miRNAs, lncRNAs, circRNAs, snoRNAs, extracellular RNAs, and m6A-related pathways add post-transcriptional and chromatin-linked layers with potential biomarker value. We synthesize these findings and discuss translational opportunities for diagnosis, stratification, flare monitoring, and therapeutic targeting, while emphasizing incomplete replication, uneven evidence across epigenetic layers, biospecimen variability, and the need for causal, longitudinal, cell-type-resolved validation.

Humans↗

PubMed2024

Whole transcriptome sequencing analyses of islets reveal ncRNA regulatory networks underlying impaired insulin secretion and increased β-cell mass in high fat diet-induced diabetes mellitus.

AIM: Our study aims to identify novel non-coding RNA-mRNA regulatory networks associated with β-cell dysfunction and compensatory responses in obesity-related diabetes. METHODS: Glucose metabolism, islet architecture and secretion, and insulin sensitivity were characterized in C57BL/6J mice fed on a 60% high-fat diet (HFD) or control for 24 weeks. Islets were isolated for whole transcriptome sequencing to identify differentially expressed (DE) mRNAs, miRNAs, IncRNAs, and circRNAs. Regulatory networks involving miRNA-mRNA, lncRNA-mRNA, and lncRNA-miRNA-mRNA were constructed and functions were assessed through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. RESULTS: Despite compensatory hyperinsulinemia and a significant increase in β-cell mass with a slow rate of proliferation, HFD mice exhibited impaired glucose tolerance. In isolated islets, insulin secretion in response to glucose and palmitic acid deteriorated after 24 weeks of HFD. Whole transcriptomic sequencing identified a total of 1324 DE mRNAs, 14 DE miRNAs, 179 DE lncRNAs, and 680 DE circRNAs. Our transcriptomic dataset unveiled several core regulatory axes involved in the impaired insulin secretion in HFD mice, such as miR-6948-5p/Cacna1c, miR-6964-3p/Cacna1b, miR-3572-5p/Hk2, miR-3572-5p/Cckar and miR-677-5p/Camk2d. Additionally, proliferative and apoptotic targets, including miR-216a-3p/FKBP5, miR-670-3p/Foxo3, miR-677-5p/RIPK1, miR-802-3p/Smad2 and ENSMUST00000176781/Caspase9 possibly contribute to the increased β-cell mass in HFD islets. Furthermore, competing endogenous RNAs (ceRNA) regulatory network involving 7 DE miRNAs, 15 DE lncRNAs and 38 DE mRNAs might also participate in the development of HFD-induced diabetes. CONCLUSIONS: The comprehensive whole transcriptomic sequencing revealed novel non-coding RNA-mRNA regulatory networks associated with impaired insulin secretion and increased β-cell mass in obesity-related diabetes.

Mice↗

PubMed2025

Identification and external validation of a prognostic signature based on myeloid-derived suppressor cells-related LncRNAs to evaluate survival prognosis and treatment efficacy in invasive breast carcinoma.

BACKGROUND: Originating in the hematopoietic tissue, myeloid-derived suppressor cells (MDSCs) significantly contribute to tumor-related immunological processes. However, their relationship with long noncoding RNAs (lncRNAs) and breast cancer remains incompletely understood. In this study, we introduced MDSCs-associated lncRNAs as novel prognostic biomarkers to assess outcomes in patients with invasive breast carcinoma (BRCA). METHODS: Information regarding BRCA cases, including clinical and genomic details, was obtained from the TCGA repository. Predictive indicators were discovered, and their reliability underwent thorough verification. A clinically useful nomogram was developed following application-based validation. Additional investigations encompassed functional analysis, TMB assessment, TME profiling, immunotherapy efficacy forecasting, and drug sensitivity testing along with target identification. Long non-coding RNA expression was measured using reverse transcription quantitative PCR. RESULTS: A risk stratification model incorporating eight MDSCs-related lncRNAs effectively predicted patient outcomes. Kaplan-Meier (K-M) survival analysis clearly indicated a much worse prognosis among patients classified as high-risk (p < 0.001). The nomogram accurately forecasted overall survival (OS). Analysis of functional enrichment revealed that pathways associated with epithelial cells showed activity among patients at higher risk. Characterization of the tumor microenvironment showed increased immune cell presence in those classified as low-risk. Conversely, individuals with greater risk displayed higher tumor mutational burden. TIDE and IPS analyses indicated superior immunotherapy responsiveness in the low-risk BRCA subgroup. Among 47 drugs with notable IC50 variations, Ribociclib, PD173074, KU-55933, NU7441, and nutlin-3a exhibited lower IC50 values within the low-risk group, whereas Lapatinib demonstrated greater efficacy among the high-risk group. Moreover, 10 potential therapeutic agents and their targets were predicted for high-risk patients. RT-qPCR validation confirmed the robustness of the model. CONCLUSIONS: We successfully verified a new model of molecular markers of MDSCs-related lncRNAs, offering critical insights for predicting outcomes and guiding therapeutic decisions in BRCA cases.

Bioinformatics↗

PubMed2026

Beyond Canonical Neoantigens: Emerging Technologies for Identification of Noncanonical Antigens and Implications for Personalized Cancer Vaccines.

Over the past decade, advances in sequencing technologies and computational pipelines enabled the development of personalized cancer vaccines (PCVs). Current PCV strategies primarily target cancer neoantigens generated by non-synonymous DNA mutations, which can result in altered amino acid sequences capable of eliciting tumor-specific immune responses. More recently, a distinct class of tumor-specific antigens (TSA), termed noncanonical or cryptic antigens, has emerged as an additional source of immunogenic targets. Unlike canonical neoantigens, noncanonical antigens typically cannot be identified by tumor/normal whole-exome sequencing, as they do not arise from classical DNA mutations. Instead, they are often associated with less well recognized and/or aberrant processes in the pathways from DNA to human leukocyte antigen (HLA)-presented peptides. Examples include transposable elements, circular RNA, translation of alternative open reading frames and/or long non-coding RNA, among others. Emerging evidence suggests that noncanonical antigens represent a substantial portion of the tumor-specific immunopeptidome and, similar to canonical neoantigens, are absent during thymic selection and can evade central tolerance and elicit T cell responses. Technological advances have increasingly facilitated the identification of noncanonical antigens. Long-read RNA sequencing reveals noncanonical transcripts by improving transcriptome assembly, while ribosome profiling provides genome-wide maps of actively translated regions, facilitating the discovery of peptides from aberrant translation events. Specialized molecular approaches enable enrichment and sequencing of circular RNAs, and immunopeptidomics using mass spectrometry allows for direct characterization of HLA-presented peptides. Together, these technological advances have led to an increasing interest in prioritizing and targeting noncanonical antigens in the next generation of PCVs. This review provides an overview of the diverse origins of TSAs beyond classical neoantigens and discusses emerging approaches that may enable the integration of these antigens in future clinical trials.

circular RNA↗

PubMed2026

Genome-wide epigenomic atlas and multi-omics responses of Eriocheir sinensis to natural extreme heat.

BACKGROUND: Global climate warming has led to increasingly frequent and prolonged extreme summer heat events, posing severe environmental challenges to aquaculture systems. Extreme summer heat can disrupt the performance of pond-cultured ectotherms. The Chinese mitten crab (Eriocheir sinensis) is an economically important freshwater crustacean, but coordinated molecular differences following contrasting natural summers remain incompletely characterized. RESULTS: We performed a comprehensive multi-omics analysis integrating meteorological monitoring, mRNA/lncRNA transcriptomics, small-RNA profiling of miRNAs, DNA methylomics, and LC-MS metabolomics in E. sinensis populations collected from Yancheng, China, between 2020 and 2024. Across the ten farms, survival was significantly lower in 2024, whereas yield and the proportion of large individuals showed nonsignificant downward trends. Gene-set analyses showed negative enrichment of cellular heat-response, protein-folding, oxidative-phosphorylation, and mitochondrial ATP-production terms in the 2024 cohort at the time of sampling. The integrated transcript annotation contained 72,240 lncRNAs and 63,833 mRNAs, and CpG was the predominant methylation context. Differential methylation analysis identified 73 regions and 185 cytosines, with hypomethylated events predominating within the significant subset. Metabolomic profiles differed between annual cohorts and mapped to carbohydrate, lipid, and amino-acid pathways. Cross-omics integration prioritized eight candidate genes-ADCY9, UNC79, UBN1, IFT52, ACO2, LOC126986070, LOC127001126, and LOC126997895-and qPCR reproduced the reported directions of expression for selected RNAs. CONCLUSION: This study provides the first integrative multi-omics framework for understanding chronic heat adaptation in E. sinensis. By linking transcriptomic, epigenomic, and metabolic remodeling, we elucidate the molecular mechanisms underlying energy imbalance, epigenetic reprogramming, and immune dysregulation during prolonged thermal stress. These findings offer valuable insights and genomic resources for breeding heat-tolerant crab strains and improving aquaculture resilience under ongoing climate change.

DNA methylation↗

PubMed2026

A modular class-aware workflow for small RNA sequencing analysis using mouse sperm as a case study.

BACKGROUND: Small RNA sequencing analysis is challenging because RNA classes differ in biogenesis, sequence redundancy, genomic organization, and annotation reliability. Integrated workflows accommodating these constraints remain limited, particularly for fragment-level and cluster-level analysis. METHODS: We present a reproducible, containerized, class-aware workflow for small RNA sequencing analysis, using mouse sperm as a case study. The workflow combines standardized preprocessing with complementary annotation and quantification strategies for microRNAs (miRNAs), transfer RNA-derived small RNAs (tsRNAs), ribosomal RNA-derived small RNAs (rsRNAs), and PIWI-interacting RNA (piRNA)-enriched genomic clusters. Using sperm small RNA data from offspring of lipopolysaccharide (LPS)-exposed male mice, we compared integrated-reference mapping, multi-class annotation, fragment-level tsRNA profiling, and genome-based piRNA cluster analysis, with custom modules for locus-aware harmonization and condition-specific cluster analysis. RESULTS: Integrated-reference mapping aligned 88.17% of reads and retained 690 features after filtering. It identified 11 differentially expressed miRNAs between LPS and controls, while other classes showed limited signal. Fragment-level profiling improved tsRNA resolution. piRNA cluster analysis identified 958 control and 940 LPS clusters, with 18 control-specific and no LPS-specific clusters. CONCLUSION: This workflow supports transparent, reproducible, class-aware interpretation of small RNA sequencing data while emphasizing cautious interpretation of piRNA-enriched signals from total small RNA sequencing.

Small non-coding RNA analysis↗

PubMed2025

Role of lncRNA PVT1 in the progression of urological cancers: Novel insights into signaling pathways and clinical opportunities.

Urologic malignancies, encompassing cancers of the kidney, bladder, and prostate, represent approximately 25 % of all cancer cases. Recent advances have enhanced our understanding of PVT1's crucial functions. Long noncoding RNAs influence both the onset and development of cancer, as well as epigenetic alterations. Recent findings have focused on PVT1's mechanism of action across several malignancies, particularly urologic cancers. Understanding the various functions of PVT1 linked to cancer is necessary for the development of cancer detection and treatment when PVT1 is dysregulated. Furthermore, recent advancements in genomic and epigenetic research have elucidated the complex regulatory networks that control PVT1 expression. Comprehending the intricate role of PVT1 Understanding the complex function of PVT1 in urologic cancers has substantial clinical implications. Here, we summarize some of the most recent findings about the carcinogenic effects of PVT1 signaling pathways and the possible treatment strategies for urological malignancies that target these pathways.

Humans↗

PubMed2026

Genome-wide detection of human 5' UTR variants that impact protein translation.

The 5' untranslated region (5' UTR) of messenger RNAs (mRNAs) plays a central role in regulating protein synthesis initiation, particularly through the Kozak sequence and upstream open reading frames (uORFs). Genetic variants within these regulatory elements could affect translation, altering gene expression and contributing to clinical phenotypes in humans. We developed a computational method called 5ULTRA (5' Untranslated Region Annotation) for analysis of whole-exome sequencing and whole-genome sequencing data to detect, annotate, and prioritize 5' UTR variants with potential translation impact. 5ULTRA identifies single-nucleotide variants, indels, and splicing variants that affect uORFs by creating or disrupting start/stop codons and that alter Kozak sequence strength of either the uORFs or the main coding sequence. 5ULTRA incorporates recent uORF databases and provides comprehensive annotations. 5ULTRA implements a machine-learning score to prioritize candidate variants with predicted effects on translation and also provides specific mechanistic predictions. The score correlates strongly with experimentally measured protein-level effects of 5' UTR variants. We applied 5ULTRA to multiple genetics datasets across diverse disease contexts, identifying candidate variants including potential cancer-driving somatic mutations predicted to decrease ABI1 level or increase NRAS abundance; common variants associated with traits such as multiple sclerosis, lung function, and cardiovascular function, by altering protein levels of TAGAP, VRTN, and SPAAR, respectively; and rare germline variants in our cohort, including a splicing variant of RPSA leading to 5' UTR sequence alteration that causes congenital asplenia and a variant of TNF that could predispose to tuberculosis.

Humans↗